AI Engineer

Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.

We're proud to be recognized as a Great Place to Work, a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you’ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Role Overview

We are seeking a skilled AI Engineer with around 2 years of experience in building and deploying machine learning and deep learning solutions. The ideal candidate should have strong programming skills, solid ML fundamentals, and hands-on experience in real-world AI applications.

Primary / Mandatory Skills (Must Have)

• Strong proficiency in Python programming
• Good understanding of Machine Learning & Deep Learning concepts
• Experience with frameworks like TensorFlow or PyTorch
• Solid knowledge of Data Structures & Algorithms
• Hands-on experience with data preprocessing and model training
• Familiarity with at least one domain:
• Natural Language Processing (NLP) or
• Computer Vision
• Experience with:
• APIs development and integration
• Model deployment in production environments
• Cloud platforms (AWS / GCP / Azure)
• Understanding of Git and standard software development practices
  

• Experience with MLOps tools (CI/CD pipelines, model monitoring, automation)
• Knowledge of Docker and Kubernetes
• Familiarity with LLMs / Generative AI:
• Prompt engineering
• Fine-tuning techniques
• Exposure to Big Data tools (e.g., Spark)
• Understanding of data engineering basics (ETL pipelines)
• Experience with:
• Vector databases
• Retrieval-Augmented Generation (RAG) pipelines
• Knowledge of model optimization techniques:
• Quantization
• Pruning
• Basic understanding of system design & scalability